Introduction to Large Language Models
Chapter 1: Understanding Large Language Models
What is Artificial Intelligence? A Brief Overview
Introducing Natural Language Processing (NLP)
Defining Large Language Models (LLMs)
How LLMs Learn from Text Data
Examples of Tasks LLMs Can Perform
Common Misconceptions about LLMs
Chapter 2: The Mechanics of LLMs (Simplified)
Representing Words: Tokens and Embeddings
Predicting the Next Word: The Core Idea
The Role of Training Data Size
Understanding Model Parameters
Introduction to Transformer Architecture (High-Level)
How Context Influences Generation
Chapter 3: Communicating with LLMs: Prompts
What is a Prompt?
Basic Prompting Techniques
Providing Instructions Clearly
Giving Examples (Few-Shot Prompting)
Controlling Output Length and Format
Common Prompting Challenges
Practice: Crafting Your First Prompts
Chapter 4: A Look at Different LLMs
Overview of Foundational Models
General Purpose vs. Specialized Models
Open vs. Closed Models: What's the Difference?
Understanding Model Size and Capabilities
Accessing Models: APIs and Interfaces
Chapter 5: Using Pre-trained LLMs
What are Pre-trained Models?
Finding and Choosing an LLM Service
Interacting via Web Interfaces
Introduction to Using LLM APIs
Sending Your First API Request
Interpreting LLM Responses
Hands-on Practical: Simple Text Generation Task
A Look at Different LLMs
Previous chapters introduced the core concepts behind Large Language Models, their simplified mechanics, and basic prompting techniques. Now, we examine the variety within the LLM space.
This chapter provides an overview of different LLM types. You will learn about:
- The concept of foundational models.
- The distinction between general-purpose models and those designed for specific tasks.
- The differences between open-access and closed, proprietary models.
- How model size often correlates with performance.
- Common ways to interact with models, focusing on Application Programming Interfaces (APIs) and web-based interfaces.
Sections
4.1 Overview of Foundational Models
4.2 General Purpose vs. Specialized Models
4.3 Open vs. Closed Models: What's the Difference?
4.4 Understanding Model Size and Capabilities
4.5 Accessing Models: APIs and Interfaces
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